{"id":"W2118775665","doi":"10.1177/1475921714546063","title":"A technique for real-time detecting, locating, and quantifying damage in large polymer composite structures made of carbon fibers and carbon nanotube networks","year":2014,"lang":"en","type":"article","venue":"Structural Health Monitoring","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Epoxy; Composite material; Materials science; Composite number; Carbon nanotube; Durability; Polymer; Structural health monitoring","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002991151,0.0004328648,0.0002264551,0.0007786917,0.0002691143,0.0002558415,0.0004460612,0.0008611283,0.0008135022],"category_scores_gemma":[0.0004815714,0.000291658,0.0001678916,0.0003522499,0.0005342677,0.0007024679,0.0003319397,0.000601158,0.0002026354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002668076,"about_ca_system_score_gemma":0.0002722553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003983255,"about_ca_topic_score_gemma":0.0008245858,"domain_scores_codex":[0.9996074,0.00003794761,0.00001249047,0.0001029059,0.0002192107,0.00002001162],"domain_scores_gemma":[0.9995399,0.0001440921,0.000152663,0.00005641758,0.00007992467,0.00002708983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004278512,0.00002291193,0.0003947059,0.00008414841,0.000005735149,0.0000765898,0.00003554468,0.0003024841,0.9709211,0.0002753894,0.0001849258,0.02765359],"study_design_scores_gemma":[0.00002074408,0.0004487227,0.003278526,0.00001364115,0.00002383289,0.001118527,0.00004187029,0.01288204,0.9774851,0.0002356066,0.004420592,0.00003073717],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2596261,0.003235702,0.7314679,0.0005094633,0.0002568064,0.0001951418,0.0002289979,0.001685406,0.002794424],"genre_scores_gemma":[0.5801263,0.001276212,0.4156073,0.0001329752,0.00007091976,0.0001629819,0.00009562602,0.00002980816,0.002497931],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008611283,"threshold_uncertainty_score":0.002721488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01162310729869953,"score_gpt":0.2765001784599181,"score_spread":0.2648770711612186,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}